Histological quantification of maize stem sections from FASGA-stained images

Maize Internode Autofluorescence at the Macroscopic Scale: Image Representation and Principal Component Analysis of a Series of Large Multispectral Images

A quantitative histology of maize stems is needed to study the role of tissue and of their chemical composition in plant development and in their end-use quality. In the present work, a new methodology is proposed to show and quantify the spatial variability of tissue composition in plant organs and to statistically compare different samples accounting for biological variability. Multispectral UV/visible autofluorescence imaging was used to acquire a macroscale image series based on the fluorescence of phenolic compounds in the cell wall. A series of 40 multispectral large images of a whole internode section taken from four maize inbred lines were compared. The series consisted of more than 1 billion pixels and 11 autofluorescence channels. Principal Component Analysis was adapted and named large PCA and score image montages at different scales were built. Large PCA score distributions were proposed as quantitative features to compare the inbred lines. Variations in the tissue fluorescence were clearly displayed in the score images. General intensity variations were identified. Rind vascular bundles were differentiated from other tissues due to their lignin fluorescence after visible excitation, while variations within the pith parenchyma were shown via UV fluorescence. They depended on the inbred line, as revealed by the first four large PCA score distributions. Autofluorescence macroscopy combined with an adapted analysis of a series of large images is promising for the investigation of the spatial heterogeneity of tissue composition between and within organ sections. The method is easy to implement and can be easily extended to other multi-hyperspectral imaging techniques. The score distributions enable a global comparison of the images and an analysis of the inbred lines' effect. The interpretation of the tissue autofluorescence needs to be further investigated by using complementary spatially resolved techniques.

Automated quantification of fluorescence and morphological changes in pretreated wood cells by fluorescence macroscopy

BACKGROUND

Lignocellulosic biomass is a complex network of polysaccharides and lignin that requires a pretreatment step to overcome recalcitrance and optimize valorisation into biobased products. Pretreatment of biomass induces chemical and morphological changes. Quantification of these changes is critical to understand biomass recalcitrance and to predict lignocellulose reactivity. In this study, we propose an automated method for the quantification of chemical and morphological parameters through fluorescence macroscopy, which was applied on wood samples (spruce, beechwood) pretreated with steam explosion.

RESULTS

Results in fluorescence macroscopy highlighted the impact of steam explosion on spruce and beechwood: fluorescence intensity of samples was highly altered, especially for the most severe conditions. Morphological changes were also revealed: shrinkage of cells and deformation of cell walls manifested as the loss of rectangularity or circular shape, for tracheids in spruce and vessels in beechwood respectively. Quantification of fluorescence intensity of cell walls and quantification of morphological parameters related to cell lumens were carried out accurately by applying the automated method onto the macroscopic images. The results showed that lumens area and circularity could be considered as complementary markers of cell deformation, and that fluorescence intensity of the cell walls could be related to morphological changes and to the conditions of pretreatment.

CONCLUSIONS

The developed procedure allows simultaneous and effective quantification of morphological parameters and fluorescence intensity of the cell walls. This approach can be applied to fluorescence macroscopy as well as other imaging techniques and provides encouraging results towards the understanding of biomass architecture.

A robust and efficient automatic method to segment maize FASGA stained stem cross section images to accurately quantify histological profile

BACKGROUND

Grasses internodes are made of distinct tissues such as vascular bundles, epidermis, rind and pith. The histology of grasses stem was largely revisited recently taking advantage of the development of microscopy combined with the development of computer-automated image analysis workflows. However, the diversity and complexity of the histological profile complicates quantification. Accurate and automated analysis of histological images thus remains challenging.

RESULTS

Herein, we present a workflow that automatically segments maize internode cross section images into 40 distinct tissues: two tissues in the epidermis, 19 tissues in the rind, 14 tissues in the pith and 5 tissues in the bundles. This level of segmentation is achieved by combining the Hue, Saturation and Value properties of each pixel and the location of each pixel in FASGA stained cross sectiona. This workflow is likewise able to highlight significant and subtle histological genotypic variations between maize internodes. The grain of precision provided by the workflow also makes it possible to demonstrate different levels of sensitivity to digestion by enzymatic cocktails of the tissues in the pith. The precision and strength of the workflow is all the more impressive because it is preserved on cross section images of other grasses such as miscanthus or sorghum.

CONCLUSIONS

The fidelity of this tool and its capacity to automatically identify variations of a large number of histological profiles among different genotypes pave the way for its use to identify genotypes of interest and to study the underlying genetic bases of variations in histological profiles in maize or other species.

Preserving the Cellular Tissue Structure of Maize Pith Though Dry Fractionation Processes: A Key Point to Use as Insulating Agro-Materials

Plant biomass has various compositions and structures at different scales (from the component organs to their constitutive tissues) to support its functional properties. Recovering each part of the plant without damaging its structure poses a challenge to preserving its original properties for differential dedicated end uses, and considerably increases its added value. In this work, an original combination of grinding based on shearing stress and separation based on particle size and density was successfully used to sort rind (65% w/w) and pith (35% w/w) from maize stem internodes. More than 97% of the rind was isolated. The pith alveolar structure was well preserved in coarse particles, making them suitable for insulation bio-based composite materials, a promising alternative to conventional nonbiodegradable insulation panels. Boards produced from the dry fractionated pith exhibited thermal conductivities like those produced from hand dissected pith, with values equal to 0.037 W·mK⁻¹ and 0.039 W·mK⁻¹, respectively. In the finest fraction (particle size <1 mm), the pith vascular bundles (around 300–400 µm in diameter) were dissociated from parenchyma cells and successfully isolated using a cutting-edge electrostatic separator. Their structures, which provide the plant structural support, make them potentially valuable for reinforcement in composite materials.

Responses of Maize Internode to Water Deficit Are Different at the Biochemical and Histological Levels

Maize feeding value is strongly linked to plant digestibility. Cell wall composition and structure can partly explain cell wall digestibility variations, and we recently showed that tissue lignification and lignin spatial distribution also contribute to cell wall digestibility variations. Although the genetic determinism of digestibility and cell wall composition has been studied for more than 20 years, little is available concerning that of tissue lignification. Moreover, maize yield is negatively impacted by water deficit, and we newly highlighted the impact of water deficit on cell wall digestibility and composition together with tissue lignification. Consequently, the aim of this study was to explore the genetic mechanisms of lignin distribution in link with cell wall composition and digestibility under contrasted water regimes. Maize internodes from a recombinant inbred line (RIL) population grown in field trials with contrasting irrigation scenarios were biochemically and histologically quantified. Results obtained showed that biochemical and histological traits have different response thresholds to water deficit. Histological profiles were therefore only modified under pronounced water deficit, while most of the biochemical traits responded whatever the strength of the water deficit. Three main clusters of quantitative trait locus (QTL) for histological traits were detected. Interestingly, overlap between the biochemical and histological clusters is rare, and one noted especially colocalizations between histological QTL/clusters and QTL for p-coumaric acid content. These findings reinforce the suspected role of tissue p-coumaroylation for both the agronomic properties of plants as well as their digestibility.

Darkfield and Fluorescence Macrovision of a Series of Large Images to Assess Anatomical and Chemical Tissue Variability in Whole Cross-Sections of Maize Stems

The proportion and composition of plant tissues in maize stems vary with genotype and agroclimatic factors and may impact the final biomass use. In this manuscript, we propose a quantitative histology approach without any section labelling to estimate the proportion of different tissues in maize stem sections as well as their chemical characteristics. Macroscopic imaging was chosen to observe the entire section of a stem. Darkfield illumination was retained to visualise the whole stem cellular structure. Multispectral autofluorescence images were acquired to detect cell wall phenolic compounds after UV and visible excitations. Image analysis was implemented to extract morphological features and autofluorescence pseudospectra. By assimilating the internode to a cylinder, the relative proportions of tissues in the internode were estimated from their relative areas in the sections. The approach was applied to study a series of 14 maize inbred lines. Considerable variability was revealed among the 14 inbred lines for both anatomical and chemical traits. The most discriminant morphological descriptors were the relative amount of rind and parenchyma tissues together with the density and size of the individual bundles, the area of stem and the parenchyma cell diameter. The rind, as the most lignified tissue, showed strong visible-induced fluorescence which was line-dependant. The relative amount of para-coumaric acid was associated with the UV-induced fluorescence intensity in the rind and in the parenchyma near the rind, while ferulic acid amount was significantly correlated mainly with the parenchyma near the rind. The correlation between lignin and the tissue pseudospectra showed that a global higher amount of lignin resulted in a higher level of lignin fluorescence whatever the tissues. We demonstrated here the potential of darkfield and autofluorescence imaging coupled with image analysis to quantify histology of maize stem and highlight variability between different lines.

High-throughput phenotyping of brachiaria grass seeds using free access tool for analyzing X-ray images

New approaches based on image analysis can assist in phenotyping of biological characteristics, serving as support for decision-making in modern agribusiness. The aim of this study was to propose a method of high-throughput phenotyping of free access for processing of 2D X-ray images of brachiaria grass (Brachiaria ruziziensis cv. Ruziziensis) seeds, as well as correlate the parameters linked to the physiological potential of the seeds. The study was carried out by means of automated analysis of X-ray images of seeds in which a macro, called PhenoXray, was developed, responsible for digital image processing, for which a series of descriptors were obtained. After the X-ray analysis, a germination test was performed on the seeds and, from this, variables related to the physiological quality of the seeds were obtained. The use of the macro PhenoXray allowed large-scale phenotyping of seed X-rays in a simple, rapid, robust, and totally free manner. This study confirmed that the methodology is efficient for obtaining morphometric data and tissue integrity data in Brachiaria ruziziensis seeds and that parameters such as relative density, integrated density, and seed filling are closely related to the physiological attributes of seed quality.

A rapid and quantitative safranin-based fluorescent microscopy method to evaluate cell wall lignification

One of the main characteristics of plant cells is the presence of the cell wall located outside the plasma membrane. In particular cells, this wall can be reinforced by lignin, a polyphenolic polymer that plays a central role for vascular plants, conferring hydrophobicity to conducting tissues and mechanical support for upright growth. Lignin has been studied extensively by a range of different techniques, including anatomical and morphological analyses using dyes to characterize the polymer localization in situ. With the constant improvement of imaging techniques, it is now possible to revisit old qualitative techniques and adapt them to obtain efficient, highly resolutive, quantitative, fast and safe methodologies. In this study, we revisit and exploit the potential of fluorescent microscopy coupled to safranin-O staining to develop a quantitative approach for lignin content determination. The developed approach is based on ratiometric emission measurements and the development of an imagej macro. To demonstrate the potential of our methodology compared with other commonly used lignin reagents, we demonstrated the use of safranin-O staining to evaluate and compare lignin contents in previously characterized Arabidopsis thaliana lignin biosynthesis mutants. In addition, the analysis of lignin content and spatial distribution in the Arabidopsis laccase mutant also provided new biological insights into the effects of laccase gene downregulation in different cell types. Our safranin-O-based methodology, also validated for Linum usitatissimum (flax), Zea mays (maize) and Populus tremula x alba (poplar), significantly improves and speeds up anatomical and developmental investigations of lignin, which we hope will contribute to new discoveries in many areas of cell wall plant research.

Parametric mapping of cellular morphology in plant tissue sections by gray level granulometry

BACKGROUND

The cellular morphology of plant organs is strongly related to other physical properties such as shape, size, growth, mechanical properties or chemical composition. Cell morphology often vary depending on the type of tissue, or on the distance to a specific tissue. A common challenge in quantitative plant histology is to quantify not only the cellular morphology, but also its variations within the image or the organ. Image texture analysis is a fundamental tool in many areas of image analysis, that was proven efficient for plant histology, but at the scale of the whole image.

RESULTS

This work presents a method that generates a parametric mapping of cellular morphology within images of plant tissues. It is based on gray level granulometry from mathematical morphology for extracting image texture features, and on Centroidal Voronoi Diagram for generating a partition of the image. Resulting granulometric curves can be interpreted either through multivariate data analysis or by using summary features corresponding to the local average cell size. The resulting parametric maps describe the variations of cellular morphology within the organ.

CONCLUSIONS

We propose a methodology for the quantification of cellular morphology and of its variations within images of tissue sections. The results should help understanding how the cellular morphology is related to genotypic and / or environmental variations, and clarify the relationships between cellular morphology and chemical composition of cell walls.

Phenotyping analysis of maize stem using micro-computed tomography at the elongation and tasseling stages

BACKGROUND

Micro-computed tomography (μCT) bring a new opportunity to accurately quantify micro phenotypic traits of maize stem, also provide comparable benchmark to evaluate its dynamic development at the different growth stages. The progressive accumulation of stem biomass brings manifest structure changes of maize stem and vascular bundles, which are closely related with maize varietal characteristics and growth stages. Thus, micro-phenotyping (μPhenotyping) of maize stems is not only valuable to evaluate bio-mechanics and water-transport performance of maize, but also yield growth-based traits for quantitative traits loci (QTL) and functional genes location in molecular breeding.

RESULT

In this study, maize stems of 20 maize cultivars and two growth stages were imaged using μCT scanning technology. According to the observable differences of maize stems from the elongation and tasseling stages, function zones of maize stem were firstly defined to describe the substance accumulation of maize stems. And then a set of image-based μPhenotyping pipelines were implemented to quantify maize stem and vascular bundles at the two stages. The coefficient of determination (R2) of counting vascular bundles was higher than 0.95. Based on the uniform contour representation, intensity-related, geometry-related and distribution-related traits of vascular bundles were respectively evaluated in function zones and structure layers. And growth-related traits of the slice, epidermis, periphery and inner zones were also used to describe the dynamic growth of maize stem. Statistical analysis demonstrated the presented method was suitable to the phenotyping analysis of maize stem for multiple growth stages.

CONCLUSIONS

The novel descriptors of function zones provide effective phenotypic references to quantify the differences between growth stages; and the detection and identification of vascular bundles based on function zones are more robust to determine the adaptive image analysis pipeline. Developing robust and effective image-based phenotyping method to assess the traits of stem and vascular bundles, is highly relevant for understanding the relationship between maize phenomics and genomics.

Crop Phenomics: Current Status and Perspectives

Reliable, automatic, multifunctional, and high-throughput phenotypic technologies are increasingly considered important tools for rapid advancement of genetic gain in breeding programs. With the rapid development in high-throughput phenotyping technologies, research in this area is entering a new era called 'phenomics.' The crop phenotyping community not only needs to build a multi-domain, multi-level, and multi-scale crop phenotyping big database, but also to research technical systems for phenotypic traits identification and develop bioinformatics technologies for information extraction from the overwhelming amounts of omics data. Here, we provide an overview of crop phenomics research, focusing on two parts, from phenotypic data collection through various sensors to phenomics analysis. Finally, we discussed the challenges and prospective of crop phenomics in order to provide suggestions to develop new methods of mining genes associated with important agronomic traits, and propose new intelligent solutions for precision breeding.

Tissue Lignification, Cell Wall p-Coumaroylation and Degradability of Maize Stems Depend on Water Status

Water supply and valorization are two urgent issues in the utilization of maize biomass in the context of climate change and replacement of fossil resources. Maximizing maize biomass valorization is of interest to make biofuel conversion competitive, and to increase forage energetic value for animal fodder. One way to estimate biomass valorization is to quantify cell wall degradability. In this study, we evaluated the impact of water supply on cell wall degradability, cell wall contents and structure, and distribution of lignified cell types in maize internodes using dedicated high-throughput tools to effectively phenotype maize internodes from 11 inbred lines under two contrasting irrigation scenarios in field trials over three years. Overall, our results clearly showed that water deficit induced significant changes in lignin content and distribution along with a reduction in lignin p-coumaroylation, thereby impacting cell wall degradability. Additionally, we also observed that responses to a water deficit varied between the lines examined, underscoring biochemical and histological target traits for plant breeding.

A new image-based tool for the high throughput phenotyping of pollen viability: evaluation of inter- and intra-cultivar diversity in grapevine

BACKGROUND

Low pollen viability may limit grapevine yield under certain conditions, causing relevant economic losses to grape-growers. It is usually evaluated by the quantification of the number of viable and non-viable pollen grains that are present in a sample after an adequate pollen grain staining procedure. Although the manual counting of both types of grains is the simplest and most sensitive approach, it is a laborious and time-demanding process. In this regard, novel image-based approaches can assist in the objective, accurate and cost-effective phenotyping of this trait.

RESULTS

Here, we introduce PollenCounter, an open-source macro implemented as a customizable Fiji tool for the high-throughput phenotyping of pollen viability. This tool splits RGB images of stained pollen grains into its primary channels, retaining red and green color fractionated images (which contain information on total and only viable pollen grains, respectively) for the subsequent isolation and counting of the regions of interest (pollen grains). This framework was successfully used for the analysis of pollen viability of a high number of samples collected in a large collection of grapevine cultivars. Results revealed a great genetic variability, from cultivars having very low pollen viability (like Corinto Bianco; viability: 14.1 ± 1.3%) to others with a very low presence of sterile pollen grains (Cuelga; viability: 98.2 ± 0.5%). A wide range of variability was also observed among several clones of cv. Tempranillo Tinto (from 97.9 ± 0.9 to 60.6 ± 5.9%, in the first season). Interestingly, the evaluation of this trait in a second season revealed differential genotype-specific sensitivity to environment.

CONCLUSIONS

The use of PollenCounter is expected to aid in different areas, including genetics research studies, crop improvement and breeding strategies that need of fast, precise and accurate results. Considering its flexibility, it can be used not only in grapevine, but also in other species showing a differential staining of viable and non-viable pollen grains. The wide phenotypic diversity observed at a species level, together with the identification of specific cultivars and clones largely differing in this trait, pave the way of further analyses aimed to understand the physiological and genetic causes driving to male sterility in grapevine.